| Literature DB >> 34134696 |
Andreas Seraphim1,2, Kristopher D Knott1,2, Anne-Marie Beirne2,3, Joao B Augusto1,2, Katia Menacho1,2, Jessica Artico2, George Joy2, Rebecca Hughes1,2, Anish N Bhuva1,2, Ryo Torii4, Hui Xue5, Thomas A Treibel1,2, Rhodri Davies1,2, James C Moon1,2, Daniel A Jones2,3, Peter Kellman5, Charlotte Manisty6,7.
Abstract
BACKGROUND: Quantitative myocardial perfusion mapping using cardiovascular magnetic resonance (CMR) is validated for myocardial blood flow (MBF) estimation in native vessel coronary artery disease (CAD). Following coronary artery bypass graft (CABG) surgery, perfusion defects are often detected in territories supplied by the left internal mammary artery (LIMA) graft, but their interpretation and subsequent clinical management is variable.Entities:
Keywords: Cardiovascular magnetic resonance; Coronary artery bypass; Grafts; Perfusion
Mesh:
Year: 2021 PMID: 34134696 PMCID: PMC8210347 DOI: 10.1186/s12968-021-00763-y
Source DB: PubMed Journal: J Cardiovasc Magn Reson ISSN: 1097-6647 Impact factor: 5.364
Baseline demographics and characteristics of coronary artery bypass graft (CABG) patients and healthy volunteers
| Patients with previous CABG | Healthy volunteers | |
|---|---|---|
| Demographics | N = 38 | N = 25 |
| Age, years (median, IQR) | 66 (60–73) | 34 (30–43) |
| Sex, n (% male) | 33 (87) | 13 (52) |
| BSA, m2 (median, IQR) | 1.9 (1.7–2.0) | 2.0 (1.8–2.0) |
| Co-morbidities | ||
| Diabetes, n (%) | 21 (55) | |
| Hypertension, n (%) | 37 (97) | |
| Hypercholesterolaemia, n (%) | 33 (87) | |
| Medication | ||
| B-blockers, n (%) | 30 (79) | |
| CCB, n (%) | 9 (24) | |
| ACE-I/ ARB, n (%) | 34 (90) | |
| Antiplatelets, n (%) | 37 (97) | |
| Presentation | ||
| Typical chest pain | 24 (63) | |
| Atypical chest pain/dyspnoea | 9 (24) | |
| NSTEACSa | 5 (13) | |
| Coronary artery bypass graft | ||
| Time from CABG, years (median, IQR) | 5 (2–11) | |
| Total number of grafts per patient, n (%) | ||
| Single graft (LIMA to LAD) | 1 (3) | |
| 2× grafts | 4 (10) | |
| 3× grafts | 23 (61) | |
| 4× grafts | 10 (26) | |
| Vein grafts per patient, n (%) | ||
| 1× vein graft | 6 (16) | |
| 2× vein grafts | 21 (55) | |
| 3× vein grafts | 10 (26) | |
| CMR parameters | ||
| LVEDVI, ml/m2 | 68 ± 12 | 77 ± 15 |
| LVMI, g/m2 | 54 ± 13 | 52 ± 10 |
| LVEF, % | 62 ± 8 | 66 ± 4 |
| Global stress MBF, ml/g/min | 1.54 ± 0.47 | 2.82 ± 0.61 |
| Global rest MBF, ml/g/min | 0.82 ± 0.21 | 0.90 ± 0.24 |
| Global MPR | 1.94 ± 0.63 | 3.22 ± 0.63 |
| LIMA–LAD (or LAD) stress MBF, ml/g/min | 1.65 ± 0.54 | 3.04 ± 0.69 |
| LIMA–LAD (or LAD) rest MBF, ml/g/min | 0.88 ± 0.22 | 1.04 ± 0.30 |
| LIMA–LAD (or LAD) MPR | 1.92 ± 0.64 | 3.04 ± 0.65 |
BSA body surface area, CCB Calcium Channel blocker, ACE-I Angiotensin converting enzyme inhibitor, ARB angiotensin receptor blocker, LVEDVI left ventricular end-diastolic volume index, LVMI left ventricular mass index, LVEF left ventricular ejection fraction, NSTEASCS non-ST elevation acute coronary syndrome
aCMR performed for evaluation of bystander disease after coronary angiography
Fig. 1Patient with patent left internal mammary artery (LIMA)-to-left anterior descending coronary artery (LAD) and evidence of inducible perfusion defect in LIMA-native LAD territories. Short axis views from base to apex (left to right). Top row (a): First pass perfusion with adenosine stress, demonstrating qualitatively a perfusion defect in the basal to mid (but not apical) LAD territory. There is a second lateral perfusion defect. Middle row (b): Perfusion mapping showing quantitatively reduced peak myocardial blood flow (MBF) in these territories. (e.g. MBF in mid antero-septum is 0.85 ml/g/min, MBF in apical septum is 1.65 ml/g/min). c Bullseye plot of stress MBF in each American Heart Association (AHA) segment. Bottom row (d): Late gadolinium enhancement (LGE) images showing no infarction. e, f Coronary angiography demonstrating patent LIMA graft (e), anastomosis site (f) and good distal run off
Predictors of stress myocardial blood flow (stress MBF) in the LIMA–LAD territory
| Independent variables | Univariate predictors | Multivariate predictors | ||||
|---|---|---|---|---|---|---|
| B | 95% CI | B | 95% CI | |||
| Age | − 0.02 | − 0.04 to (− 0.001) | − 0.15 | − 0.03 to 0.003 | 0.097 | |
| Native LAD occlusion | − 0.47 | − 0.79 to (− 0.15) | − 0.41 | − 0.73 to (− 0.09) | ||
| LVEF | − 0.02 | − 0.04 to 0.04 | 0.118 | − 0.02 | − 0.04 to (− 0.005) | |
| Diabetes | − 0.18 | − 0.53 to 0.18 | 0.320 | − 0.18 | − 0.49 to 0.14 | 0.261 |
| LVMI | − 0.01 | − 0.02 to 0.01 | 0.177 | |||
| Sex (Male) | − 0.31 | − 0.83 to 0.21 | 0.236 | |||
| Beta-blockers | 0.30 | − 0.016 to 0.76 | 0.193 | |||
LIMA–LAD territory (average of stress MBF in myocardial segments 1,2,7,8,13,14)
Bold p-values are statistically significant
Fig. 2Box-plot showing stress MBF in the LIMA–LAD territory (AHA 1,2,7,8,13,14) depending on native LAD status. Total occlusion of the native LAD was associated with significant reduction in stress MBF. Error bars represent 95% CI
Fig. 3Stress MBF within the LIMA–LAD territory in each myocardial level (basal, mid, apex). Total occlusion of the native LAD was associated with a reduction in peak MBF of the basal and mid-but not apical LAD segments. Error bars represent 95% CI
Absolute change in MBF and MPR observed by re-processing the perfusion map data using an increased maximum arterial time delay threshold (from 2.5 to 5 s)
| All CABG cases (n = 38) | ||||||
|---|---|---|---|---|---|---|
| Myocardial territory | Change in stress MBF (ml/g/min) | p value | Change in rest MBF (ml/g/min) | p value | Change in MPR | p value |
| Global | 0.05 (0.02–0.08) | < 0.001 | 0.06 (0.04–0.09) | < 0.001 | − 0.06 (− 0.11 to (− 0.01)) | < 0.001 |
| LIMA–LAD | 0.05 (0.01–0.09) | < 0.001 | 0.05 (0.03–0.08) | < 0.001 | − 0.05 (− 0.10 to 0.00) | < 0.001 |
| LIMA–LAD | 0.06 (0.00–0.09) | < 0.001 | 0.05 (0.03–0.11) | < 0.001 | − 0.03 (− 0.08 to 0.00) | 0.063 |
| Healthy subjects (n = 25) | ||||||
| Global | 0.01 (0.00–0.03) | < 0.001 | 0.09 (0.06–0.11) | < 0.001 | − 0.25 (− 0.35 to (− 0.20)) | < 0.001 |
| LAD | 0.01 (0.00–0.01) | 0.001 | 0.06 (0.05–0.09) | < 0.001 | − 0.18 (− 0.26 to (− 0.12)) | < 0.001 |
Results shown as median and interquartile range